1. Field of the Invention
This invention relates to an image processing apparatus which performs pseudo-halftone processing of multivalue image data.
2. Description of the Related Art
An error diffusion method and an average density approximation method have been proposed as pseudo-halftone processing methods in an image processing apparatus, such as a facsimile apparatus, a digital copier or the like.
In the error diffusion method, as disclosed in "An Adaptive Algorithm for Spatial Gray Scale", SID 75 Digest, pp. 36-37, by R. Floyd and L. Steinberg, multivalue image data of a target picture element are binary-coded (converted into either the densest level or the lightest level), predetermined weighting processing is performed on the binarization error (the difference between the binary-coded level and the multivalue image data before the binary-coding processing), and the resultant weighted data are added to the data of picture elements near the target picture element.
In the average density approximation method, as described in Japanese Patent Application Public Disclosure (Kokai) No. 57-104369 (1982), each weighted average value of a target picture element and neighboring picture elements when the target picture element is binary-coded to black or white is obtained using already binary-coded data near the target picture element, and image data of the target picture element are binary-coded using the average of the two average values as the binarization threshold value.
Since the above-described error diffusion method is a method of correcting an error between input image data and output image data, it is possible to preserve the densities of the input image in the output image, and to provide an image having excellent resolution and gradation.
In the error diffusion method, however, a large amount of two-dimensional calculation must be performed when correcting for (distributing) the errors between input image data and output image data. Hence, this method has the disadvantage that the configuration of hardware becomes very complicated due to the large amount of processing required.
Since the average density approximation method performs calculation using binary data after binary-coding processing, it is possible to simplify the configuration of hardware, and to realize high-speed processing due to the extremely small amount of needed processing.
In the average density approximation method, however, binary-coding processing is performed while approximating a target picture element to an average value of a region including the target picture element. Hence, this method has the disadvantages that the number of gradation is limited, and that a peculiar low-frequency texture is produced for an image having a gentle density variation, degrading picture quality.
In order to remove the above-described disadvantages, the assignee of the present application has filed patent applications on inventions for correcting an error produced by binary-coding processing by the average density approximation method in CFO 6620US (application No. 476,766, filed Feb. 8, 1990), CFO 6621US (application No. 476,618, filed Feb. 7, 1990), CFO 6773US (application No. 514,616, filed Apr. 26, 1990), CFO 6774US (application No. 515,222, filed Apr. 27, 1990), CFO 7074US (application No. 587,217, filed Sep. 24, 1990), and CFO 7075US (application No. 587,858, filed Sep. 25, 1990).
In general, in a conventional method, when it is intended to obtain a reduced binary-coded image, some of the binary-coded data after binary-coding processing are removed, or a reading system controls data to be input in advance. Hence, the conventional method has the disadvantage that the hardware becomes complicated.
Furthermore, the conventional method has the disadvantages that fine lines disappear and that gradation deteriorates when reduction is performed by simple removal of some data.
Particularly, in the above-described average density approximation method, binary data after binary-coding processing are used also for the subsequent binary-coding processing. Hence, this method has the disadvantage that simple removal of some data in reduction influences even the subsequent binary-coding processing.
The method also has the disadvantages that when reduction is performed by simple removal of some data, fine lines might disappear and gradation might deteriorate. Such phenomena appear more pronouncedly as the reduction ratio is smaller.